If you’ve seen some of my recent posts or are following me on Twitter, you’ll know that I’ve become somewhat obsessed with analyzing the relationship between quarterback and receiver ADPs. You can look at the previous articles to dig into the methodology, which includes adjustments for expected QB rushing production and running back usage in the passing game…. Membership Required You must be a member to...

I’ve been looking at passing-game arbitrage opportunities lately, and among other things I found that Joe Flacco’s ADP looks extremely overvalued relative to his receivers’.[1]Wide receivers and tight ends I listed a few caveats in the analysis, the two most significant being that the relationship between quarterback and receiver ADPs does not account for QB rushing production, or passing production to running backs. Rather than just leave…...

Recently I wrote a piece on the relationship between passing-game ADPs, specifically comparing a quarterback’s ADP versus that of his collective wide receivers and tight ends. I highlighted a few potential arbitrage opportunities, and I concluded that Joe Flacco should be avoided based on the fact that he was being drafted too high in comparison to his receivers, none of whom are going in the first 100 picks…. Membership Required...

I’ve been thinking a lot lately about the benefit of de-emphasizing player-specific analysis that is largely baked into ADP, and instead focusing on relationships between players’ prices to identify historically favorable risk/reward opportunities. I’ve already looked at how prediction markets can help us find find undervalued rookies and what usage tendencies can tell us about the value of running backs in 2015. This arbitrage analysis was sparked…...

Recently we were all standing around the RotoViz virtual water cooler, shooting the breeze on weighting prospect similarity variables, dealing with comment trolls,[1]This is my preferred method. and properly calculating draft equity,[2]Get a glimpse of the newly added “Exposure” tab, part of our indispensable Best Ball ADP App when Fantasy Douche wondered aloud if Breshad Perriman’s redraft ADP is historically cheap considering his expected draft position. Around…...

Earlier this week I posted usage visualizations for running backs drafted in the first, second, and third rounds of current MFL10s.[1]ADP data based on drafts from the most recent week: 3/18/15-3/24/15 Those visualizations gave us an idea of which RBs have the potential for elite usage this year, with the knowledge that RB production is closely tied to usage and RBs with elite usage (over…...

I recently wrote a post on Justin Forsett, Matt Forte, and “The Trestman Effect” where I looked at usage (snap percentage) versus PPR points. The correlation league-wide was even stronger than I expected, with the vast majority of running backs scoring within +/- 50 points of the regression line. Usage is particularly important in PPR leagues because flukier types of scoring like touchdowns are de-emphasized, and reception points…...

For most of the early offseason I’ve been happy to draft Justin Forsett in the 4th round of early MFL10s under the assumption that if he re-signed with the Ravens he’s have top-5 potential in Marc Trestman’s offense. Now that he has, let’s take a deeper look at his potential and how “The Trestman Effect” benefited Matt Forte. Anyone lucky enough to have drafted Forte the…...

Justin Winn wrote an article earlier this year on whether you should draft rookie RBs, like Todd Gurley, in MFL10s. I think the same should be asked of rookie receiving options. I decided to look at how rookie wide receiver and tight end MFL10 ADPs fluctuated over the off-season last year to see if there may be hidden pockets of value in this year’s rookie…...

Last year I sliced and diced some data that Papa Viz put together on average scores for different roster allocations from a 350-league sample of 2013 My Fantasy League MFL10s. Luckily, Fantasy Douche has again done the heavy lifting this year, collecting the data from a 900-league sample. I filtered the data and isolated each roster position in order to calculate the average scores for all teams…...